Priority Rule Generation with a Genetic Algorithm to Minimize Sequence Dependent Setup Costs

Setup costs are a crucial factor in many branches of industry and frequently sequence dependent. However, the empirical acquisition of setup costs is inaccurate and not practicable for companies with large product portfolios operating in volatile markets. We therefore propose an abstract model for the estimation of such sequence dependent setup costs and subsequently apply dispatching and scheduling strategies to generate optimized production sequences. Both approaches are tested on randomly generated test instances and a real-world production scenario.